Error bars indicate SDs.
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Hakonarson H, Thorvaldsson S, Helgadottir A, et al. Effects of a 5-Lipoxygenase–Activating Protein Inhibitor on Biomarkers Associated With Risk of Myocardial InfarctionA Randomized Trial. JAMA. 2005;293(18):2245–2256. doi:10.1001/jama.293.18.2245
Context Myocardial infarction (MI) is the leading cause of death in the world.
Variants in the 5-lipoxygenase–activating protein (FLAP) gene are associated
with risk of MI.
Objective To determine the effect of an inhibitor of FLAP on levels of biomarkers
associated with MI risk.
Design, Setting, and Patients A randomized, prospective, placebo-controlled, crossover trial of an
inhibitor of FLAP (DG-031) in MI patients who carry at-risk variants in the
FLAP gene or in the leukotriene A4 hydrolase gene. Of 268 patients
screened, 191 were carriers of at-risk variants in FLAP (87%) or leukotriene
A4 hydrolase (13%). Individuals were enrolled in April 2004 and
were followed up by designated cardiologists from a university hospital in
Iceland until September 2004.
Interventions Patients were first randomized to receive 250 mg/d of DG-031, 500 mg/d
of DG-031, 750 mg/d of DG-031, or placebo. After a 2-week washout period,
patients received DG-031 if they had received placebo first or placebo if
they had received DG-031 first. Treatment periods lasted for 4 weeks.
Main Outcome Measures Changes in levels of biomarkers associated with risk of MI.
Results In response to 750 mg/d of DG-031, production of leukotriene B4 was significantly reduced by 26% (95% confidence interval [CI], 10%-39%; P = .003) and myeloperoxidase was significantly
reduced by 12% (95% CI, 2%-21%; P = .02).
The higher 2 doses of DG-031 produced a nonsignificant reduction in C-reactive
protein (16%; 95% CI, −2% to 31%; P = .07)
at 2 weeks. However, there was a more pronounced reduction (25%; 95% CI, 5%-40%; P = .02) in C-reactive protein at the end of
the washout period that persisted for another 4 weeks thereafter. The FLAP
inhibitor DG-031 was well tolerated and was not associated with any serious
Conclusion In patients with specific at-risk variants of 2 genes in the leukotriene
pathway, DG-031 led to significant and dose-dependent suppression of biomarkers
that are associated with increased risk of MI events.
Myocardial infarction (MI) is now the leading cause of death in the
world.1,2 We recently reported
the identification of a gene variant that predisposes patients to MI.3 The gene was mapped with a genome-wide linkage scan
without any assumption about the biological pathways contributing to the pathogenesis
of MI. The gene encodes the 5-lipoxygenase–activating protein (FLAP)
and its risk variant results in an almost 2-fold increased risk of MI.3 The leukotriene pathway, through FLAP, leads to the
production of leukotriene B4, which is one of the most potent chemokine
mediators of arterial inflammation.4,5
We have shown3 that MI patients produce
more leukotriene B4 than controls, suggesting that the at-risk
variant up-regulates the leukotriene pathway. By inhibiting the function of
FLAP as a result of down-regulation of the leukotriene pathway, the risk of
MI may be decreased in those predisposed to the variant.
This trial was designed to determine whether the genetic defect that
predisposes patients to MI through the leukotriene pathway could be compensated
by inhibiting FLAP. Of several available inhibitors of FLAP, we tested DG-031,
which has been used in asthma clinical trials and has been shown to be safe
and well tolerated.6,7 In this
trial, we examined the influence of DG-031 on biomarkers that have been shown
to correlate with risk of cardiovascular events.8-12 We
also performed an open-label, 1-week follow-up study of 75 patients with the
same baseline characteristics and eligibility criteria to further assess the
effects of DG-031 on biomarkers that are associated with MI risk.
All patients had a history of MI and were carriers of specific MI-associated
variants of FLAP and/or leukotriene A4 hydrolase. The recruitment
process included individuals who had previously participated in a population-based
study of the genetics of MI.3 Selection of
participants for the study was based on previous haplotype and genotype information
from the databases of Decode Genetics Inc (Reykjavik, Iceland). Of the patients
enrolled, 87% carried some at-risk variant of FLAP. The at-risk variants A3
and AF include 3 and 2 single nucleotide polymorphism (SNP) markers, respectively,
of the at-risk haplotype HapA, which have been previously described.3 Apart from FLAP, we have also observed that allele
A of the SNP SG12S25 in the leukotriene A4 hydrolase gene is associated
with MI (H.H., unpublished data, 2004). In particular, among the 13% of individuals
who did not carry an at-risk haplotype of FLAP all but one carried the at-risk
Four SNP markers were genotyped to define the at-risk variants of the
study participants (Table 1). The haplotypes
carried by each individual were estimated using the Nested Models (NEMO) software
program (version 1.01, Decode Genetics)13 and
902 in-house population controls. Among more than 900 patients identified
as eligible by clinical and genotypic criteria, 640 provided written informed
consent granting permission to use their genetic and medical data. The genotypes
for the FLAP and leukotriene A4 hydrolase genes were subsequently
reconfirmed and carriers of at-risk variants in the FLAP gene, the leukotriene
A4 hydrolase gene, or both, were eligible for this study if they
also met the other inclusion criteria but met none of the exclusion criteria
(Box). The study protocol
was approved by the National Bioethics Committee of Iceland, the Icelandic
Data Protection Agency, and the Icelandic Medicines Control Agency. All patients
who participated in the DG-031 trial gave their informed consent.
Age between 40 and 75 years.
Carrier of 5-lipoxygenase–activating protein
and/or the leukotriene A4 hydrolase variants.
Documented coronary artery disease with previous
history of myocardial infarction.
Women of childbearing potential must have a negative
urine pregnancy result at visit 1 and are required to use 2 adequate barrier
methods of contraception throughout the study.
Understanding of the study procedures and agreement
to participate in the study by providing written informed consent.
Confirmed diagnosis of congestive heart failure.
Any experimental treatment within 2 months of screening
or planned during the following 3 months.
Acute cardiovascular event (such as acute coronary
syndrome, myocardial infarction, or stroke) within 1 month prior to enrollment.
Elevated creatine kinase above 3-fold the upper limit
of normal. Other liver function tests and kidney function tests above 1.5-fold
the upper limit of normal.
Immunocompromised individuals, including those known
to have human immunodeficiency virus or have a malignant disease and/or taking
chronic immunosuppressive therapy.
Individuals known to have positive serological results
for hepatitis B surface antigen or hepatitis C virus.
Treatment with immunosuppressive cytotoxic drugs
or corticosteroids within 6 weeks or during conduct of the study.
Major surgery within 6 weeks prior to enrollment.
Any other major intercurrent illness or condition,
which may interfere with the individual’s participation in this study.
Individuals not willing to return for follow-up or
with known history of noncompliance.
Patients who consume more than 2 alcoholic drinks
per day or 10 or more drinks per week or history of alcohol abuse within the
past 2 years. Patients must agree to comply with the restrictions on alcohol
(≤2 drinks per day and <10 drinks per week and no alcohol intake within
48 hours of study visits).
Pregnant or lactating women.
Poor mental function or any other reason to expect
difficulty in complying with the requirements of the study.
The first patient was enrolled on April 5, 2004, and the study follow-up
phase was completed on September 14, 2004. All study participants lived in
the metropolitan area or its neighboring townships of Reykjavik, Iceland.
All participants were followed up at their outpatient or private clinics by
the designated cardiologists from the Landspitali University Hospital (Reykjavik,
Iceland). Participants had previously participated in a study on the genetics
of MI.3 A medical history was completed, including
detailed information on comorbidities, concomitant medications, and cardiovascular
history, including current status.
All participants fasted prior to study visits and refrained from taking
medications. Cardiologists examined the patients at each study visit and completed
case report forms. All blood samples were collected and processed immediately
after sampling. The chemistry analyses, hematologic tests, and urine tests
were performed at the Icelandic Heart Association (study site), whereas the
majority of biomarker measurements were performed at Decode Genetics. Lipoprotein
phospholipase A2 (Lp-PLA2) was measured at Diadexus
(San Francisco, Calif). All blood specimens used for the biomarker studies
were processed at Decode Genetics within 2 hours of collection. The trial
was double-blinded and treating physicians were blinded to randomization.
The FLAP inhibitor DG-031 used in this study (formerly known as BAY
x 1005) was licensed from Bayer Health Care AG (Leverkusen, Germany). DG-031
acts by binding to the FLAP protein and prevents translocation of 5-lipoxygenase
from the cytosol to the cell membrane. The drug competes for binding sites
on the cell membrane with 5-lipoxygenase, and thus is a functional competitive
inhibitor. This drug had been in development for asthma treatment and more
than 20 studies have been conducted, including a small phase 3 study (Bay
x 1005 study report No. PH-28207, unpublished data, 2005) that lasted for
12 months. The drug was found to be safe and well tolerated in asthma patients.
It has not been marketed and there have been no previous studies on DG-031
for use in cardiovascular disease. Bayer had no involvement in the current
Patients who met the study eligibility criteria were enrolled and randomized
into 6 treatment sequences (Figure 1);
a sequence with DG-031 first and then placebo and a sequence with placebo
first and then DG-031 for each of the 3 dosages: 250 mg/d (n = 64), 500 mg/d
(n = 64), and 750 mg/d (n = 63). All patients received 3 tablets per day.
The treatment periods lasted for 4 weeks and were separated by a 2-week
washout period. The placebo tablets were identical to the DG-031 tablets in
shape, color, form, and taste. Participants were permitted to take other medications
and adhere to the treatment plan prescribed by their cardiologist prior to
enrollment. The crossover study design is summarized in Figure 1.
The primary objective was to determine whether the FLAP inhibitor DG-031
has a statistically significant effect compared with placebo on 1 or more
biomarkers of MI risk (ionomycin-induced leukotriene B4 and myeloperoxidase
release by neutrophils ex vivo; myeloperoxidase,
C-reactive protein [CRP], N-tyrosine, Lp-PLA2, or
serum amyloid A; or leukotriene E4 in urine). The secondary objective
was to determine whether the effect of DG-031 was dose-dependent. The tertiary
objective was to assess other biomarkers, including those associated with
inflammation. Evaluation of safety and tolerability of DG-031 was also performed.
All data were analyzed according to a preestablished statistical analysis
plan and according to the intention-to-treat principle. Each dosage group
in the study, as well as pooled sets (combining dosage levels), was considered
for the primary analysis. The crossover design contains sets of patients who
received treatment first and then placebo and those who received placebo first
and then treatment. Biomarkers of MI risk were measured at the end of the
treatment periods (visits 4 and 7) and were used as primary response variables.
The difference between DG-031 and placebo treatment was the primary outcome
and was assessed separately for each biomarker. Treatment effect was tested
using a 2-sample t test on the period differences
for suitably transformed response variables under an assumption of normality
of the transformed data. We report treatment effect as half of the observed
mean difference in the 2-sample t test with a 95%
confidence interval (CI). Prespecified tests for carryover were performed
and are reported separately from the results of the primary analysis. All
hypotheses were tested at a 2-sided nominal significance level of .05 and P values based on t tests are
reported. The R Statistical System (version 1.9.1, R Foundation for Statistical Computing,
http://www.R-project.org) was used for all statistical
For the primary efficacy end points in which the effects of the 2 highest
dosage levels on 10 primary variables were studied, a randomization test was
performed that corrects for multiple testing and ensures that the key results
are not affected by distributional concerns. In particular, 1 million permutations
of the patients into the different study tracks were performed, which generated
a reference distribution for the maximum of the 10 t statistics
of the biomarkers under the null hypothesis of no drug effect. By comparing
the observed t statistic of each of the 10 biomarkers
to this reference distribution, empirical P values
were computed. It was considered likely that experimental manipulations would
alter the effect of the drug on 2 of the primary markers; this was indeed
the case and we report 8 of the 10 primary markers but all 10 are included
in the randomization test.
To cancel out the potential interference from systematic seasonal effects
(ie, seasonal allergies that could affect levels of inflammatory biomarkers),
carryover effects were also studied in post hoc analyses with t tests that compare measurements of the groups who received DG-031
first and then placebo with the measurements of the groups who received placebo
first and then DG-031. To estimate the effect of DG-031 at visit 3 for the
groups who received DG-031 first and then placebo after the crossover, measurements
taken at visit 2 were subtracted from measurements taken at visit 3. Similarly
to estimate the effect of DG-031 at visit 4, measurements taken at visit 2
were subtracted from measurements taken at visit 4. To estimate the effects
at visit 5, measurements taken at visit 2 were subtracted from measurements
taken at visit 5. For estimating the effect at visit 6, we used the following
formula: [(visit 6 − visit 2) + (visit 3 − visit 2)]. Note that
visit 6 from the groups who received placebo first includes the effect of
DG-031 after 2 weeks that cancels out the effect of DG-031 at visit 3 from
the groups who received DG-031 first. Similarly to estimate the effect of
DG-031 at visit 7, we used the formula: [(visit 7 − visit 2) + (visit
4 – visit 2)]. Only measurements from the groups who received the 2
higher DG-031 dosages first and then placebo were used for all visits. Measurements
from all the groups who received placebo first were used for visits 3, 4,
and 5 because each group received the same placebo until visit 5. However,
similar to patients who received DG-031 first, only measurements from the
patients who received placebo first and were assigned to the 2 higher DG-031
dosage groups were used for visits 6 and 7.
The sample size for this study was chosen so that each of the 3 dosage
groups provided at least 80% power (2-sided P = .05)
after a dropout rate of up to 5% to detect a relative reduction of 15% for
a log-normal response variable, given that an assay for that variable has
a coefficient of variation of 20% and the intraperson coefficient of variation
is as high as 25%. Based on these assumptions, the recruitment target was
180 patients with randomization into 3 dosage groups.
A study flowchart is shown in Figure 1.
At the enrollment visit, an independent study nurse who was blinded to the
drug content dispensed medication kits according to a computer-generated randomization
list. Randomization of study patients was stratified according to sex. A permuted
block design with a block size of 12 was used. All biomarkers were transformed
using a shifted log transform (transformed value is natural log of original
value plus a shifting constant for each assay). Missing data were filled in
using a simple last observation carried forward scheme. If no previous measurement
existed, the next observation was carried back. Statistical outliers for data
sets were used based on the interquartile range distance from the median prior
The SNPs genotyping within the FLAP and leukotriene A4 hydrolase
genes was performed using the SNP-based Taqman platform (Table 1).3 The enzyme-linked immunosorbent and mass spectrometry
assays used are described elsewhere.14-31 Apart
from measurements in plasma, leukotriene B4 and myeloperoxidase
were also measured in whole blood preparations ex vivo following
ionomycin-activation of leukocytes. Both dose- and time-dependent stimulations
were performed to determine the maximum leukotriene B4 and myeloperoxidase
output of the cells. Correction was made for white blood cell count because
the amount of these mediators produced is proportional to the number of cells
in a fixed volume. The adjustment on the log scale was based on a linear model,
with coefficients determined empirically at time of blinded review. Several
tertiary markers were also measured including: interleukin (IL) 6, IL-12p40,
tumor necrosis factor α, matrix metalloproteinase 9, soluble intercellular
adhesion molecule, soluble vascular cell adhesion molecule, platelet selectin,
endothelial selectin, monocyte chemotactic protein 1, and oxidized low-density
lipoprotein (LDL) cholesterol.
After completion of the double-blind study reported herein, an open-label
randomized study was conducted in an independent cohort of patients with the
same eligibility criteria to measure several of the same biomarkers. This
study included 75 patients in 3 groups of equal size, each with a distinct
dosing regimen of active drug, including the 750 mg/d dose. Each patient received
DG-031 for 8 days; there was no placebo group. The primary objective of this
study was to determine pharmacokinetic parameters of DG-031 in 3 different
doses, as well as to assess the pharmacokinetic/pharmacodynamic relationship
between DG-031, leukotriene B4, and myeloperoxidase.
A total of 191 patients were enrolled and 172 completed all 8 visits.
All 191 participants were analyzed as randomized in the intention-to-treat
analysis using the last observation carried forward approach. There were no
differences in the baseline characteristics of the study participants between
the study sequences (Table 2) or in
baseline values of the biomarker data (Table 3).
For the primary efficacy end point, 10 variables (Table 4) were considered in the pooled set of patients in the 500
mg/d and 750 mg/d groups (Table 5).
The primary efficacy end point of the study was confirmed by showing that
DG-031 reduces levels of leukotriene B4 produced by ionomycin-activated
neutrophils ex vivo for the pooled set of the 500
mg/d and 750 mg/d dosage groups by 17% (95% confidence interval [CI], 6%-27%;
nominal P = .004), which is statistically
significant after correction for multiple testing using the randomization
procedure (corrected P = .02; Table 6). Leukotriene E4 levels in
urine were increased by 21% for the pooled set of dosage groups (95% CI, 13%-30%; P<.001 [corrected P<.001]).
For the 750 mg/d of DG-031 group, production of leukotriene B4 was reduced by 26% (95% CI, 10%-39%; P = .003)
and myeloperoxidase production was reduced by 12% (95% CI, 2%-21%; P = .02) (Table 4).
Treatment with 750 mg/d of DG-031 also significantly reduced serum soluble
intercellular adhesion molecule 1 (P = .03),
but no effects were observed on other tertiary markers. Levels of Lp-PLA2 increased by 9% (95% CI, 3%-16%; P = .006)
in response to 750 mg/d of DG-031. Similarly LDL cholesterol increased by
8% (95% CI, 4%-12%; P<.001) with 750 mg/d of DG-031.
In contrast, the effects of the 2 lower doses (250 mg/d and 500 mg/d) on Lp-PLA2 were not significant.
In response to 750 mg/d of DG-031, leukotriene E4 levels
in urine increased by 27% (95% CI, 15%-40%; P<.001).
Significant correlation was observed between the change of leukotriene B4 and myeloperoxidase production (r = 0.62;
95% CI, 0.51-0.70; P<.001). This correlation was
also observed when considering only those taking DG-031 when the range of
these changes was larger. However, this correlation was also observed for
these variables at baseline. The higher 2 DG-031 dosage groups had reductions
in CRP by 16% (95% CI, −2% to 31%) at 2 weeks, although this is not
significant (P = .07). Reductions in CRP
were more pronounced at the end of the washout period (25%; 95% CI, 5%-40%; P = .02) and persisted for another 4 weeks thereafter.
All effects on biomarkers were measured at the Cmin plasma concentration
A test for the carryover effects from the treatment phase to the placebo
phase was performed as a 2-sample t test on the differences
between visits 2 and 5 for patients taking DG-031 first and then placebo.
The cohort taking DG-031 consists of only patients receiving 500 mg/d and
750 mg/d of DG-031 during the trial and the placebo cohort includes all patients.
The resulting P values and 95% CIs for the carryover
effect are provided in Table 7 (data
were not available for Lp-PLA2 and N-tyrosine).
No carryover effects were observed with leukotriene B4 and myeloperoxidase.
In contrast, significant carryover effects were observed for CRP and serum
amyloid A, with a reduction in CRP that was significant at the 5% level (P = .02). Serum amyloid A showed similar carryover
effects that were slightly below this significance level (P = .05).
Figure 2 shows the estimated mean
effects on CRP and serum amyloid A for the patients receiving the 2 higher
dosage levels of DG-031 during the first treatment period. Measurements from
patients receiving placebo first also contribute to these estimates to cancel
out potential seasonal effects. For visits 3 (after 2 weeks of receiving treatment)
and 4 (after 4 weeks of receiving treatment), this constitutes the treatment
effect, whereas the carryover effects appear between visits 5 to 7.
Among patients who took DG-031 during the first part of the study, the
CRP levels decreased at visits 3 and 4, but not significantly so. The reduction
became more pronounced and significant at visit 5, approximately 25% [95%
CI, 5%-40%; P = .02). This reduction effect
continued until visit 7, during the time the patients were receiving placebo.
This reduction effect is part of the reason that the drug effect was not detected
in the primary analysis, which did not take this scenario into account. The
design of this trial does not have sufficient power for studying such effects,
which are reflected in the large SEs in the estimates, particularly for visits
6 and 7. Even though measurements at visits 3 and 6 are not available for
serum amyloid A, the observed changes of CRP and amyloid A between visits
2 and 5 are highly correlated (r = 0.68;
95% CI, 0.51-0.80; P<.001). Hence it appears that
the drug has similar effects on both biomarkers.
Of the75 patients in the open-label follow-up study who received DG-031
for 8 days, 75 patients completed the study and provided complete data, including
25 patients in the 375 mg/d group and 50 patients in the 750 mg/d group. The
750 mg/d group was split into 2 subcohorts of 25 patients each (375 mg twice
daily and 250 mg 3 times daily). Compared with baseline values, CRP levels
after 8 days were reduced by 28% (95% CI, 5%-45%) in the 375 mg/d group (P = .02) and by 38% (95% CI, 9%-57%) in the 250
mg 3 times daily group (P = .02). However,
no reduction (95% CI, −48% to 32%) was observed in the 375 mg twice
daily group. A few individuals demonstrated increases in CRP levels; the lymphocyte
counts were also elevated suggesting that viral processes may have been at
play possibly increasing sampling variation. While the difference among the
effects of the 3 dosage groups is not statistically significant (analysis
of variance P = .16), the overall reduction in CRP
levels for all 75 patients is significant (23%; 95% CI, 6%-37%; P = .01).
After 8 days of treatment, plasma myeloperoxidase levels were not significantly
changed. However, at 6 hours after DG-031 administration on day 8, plasma
myeloperoxidase levels were reduced by 3% (95% CI, −40% to 32%) in the
375 mg/d group (P = .88), by 21% (95% CI, −6%
to 41%) in the 375 mg twice daily group (P = .11),
and by 31% (95% CI, 16%-44%) in the 250 mg 3 times daily group (P<.001). For the full cohort of 75 patients, myeloperoxidase plasma
levels measured 6 hours after administration were reduced by 20% (95% CI,
5%-32%; P = .01).
There was no difference in serious adverse events between the dosage
groups. In particular, no difference was detected in levels of liver transaminases
between the groups receiving active drug or placebo. The only symptom that
was reported significantly more often while taking DG-031 was dizziness, which
was experienced by 6 patients, compared with no reported events by patients
while taking placebo (P = .03). This did
not interfere with the daily activities of these patients.
This phase 2 clinical trial was designed to determine whether the effect
of the variant of FLAP that predisposes individuals to MI3 could
be neutralized, ie, could DG-031 be used to down-regulate FLAP in the leukotriene
pathway as shown by a reduction in leukotriene B4 levels. Furthermore,
we examined the influence of DG-031 on biomarkers that have been correlated
with risk of MI. Our results demonstrate that in patients with at-risk FLAP
and leukotriene A4 variants, DG-031 has a significant and dose-dependent
effect at the cellular, whole blood, and urinary metabolite level: a 26% reduction
in leukotriene B4 production by activated neutrophils (95% CI,
10%-39%; P = .003); a 12% reduction in
myeloperoxidase in whole blood (95% CI, 2%-21%; P = .02);
and a 27% increase in urinary leukotriene E4 level (95% CI, 15%-40%; P<.001). Following discontinuation of the FLAP inhibitor
DG-031, there was evidence of a persistent effect on high-sensitivity CRP
(P = .02) and serum amyloid A (P = .05).
Myocardial infarction occurs as a result of the development of atherosclerotic
plaque fissure, erosion, or frank rupture.32-34 When
such arterial injury manifests, a platelet-thrombosis response is mounted
and occlusion of a main epicardial coronary artery leads
to myocardial damage. In recent studies,8-11,35 many
distinct mediators of arterial inflammation have been implicated, and such
mediators have been shown to be independently associated with the risk of
MI. Such cytokines and chemokines include CRP, serum amyloid A, myeloperoxidase,
and intercellular adhesion molecule. Furthermore, at the arterial tissue level,
5-lipoxygenase and FLAP have been shown to track with more complex coronary
arterial plaques, reflecting the contribution of leukotrienes to the arterial
pathology.36,37 Both mRNA and
protein expressions of 5-lipoxygenase, FLAP, and the leukotriene A4 hydrolase
genes are increased several fold in resident tissue cells and infiltrating
cells of vascular plaques, including cells in the coronary arteries.38 This is the part of the pathway that produces leukotriene
B4, whereas the molecules in the leukotriene C4 synthase
part of the pathway do not show evidence of expression changes. Moreover,
unstable vascular plaques show abundant accumulation of activated neutrophils
that produce leukotriene B4, which in turn induces the expression
and activation of myeloperoxidase (this is essentially limited to neutrophils
themselves) that subsequently generates potent oxidants such as hydrochloric
acid and also oxidizes LDL cholesterol and renders them proinflammatory in
Myeloperoxidase also inactivates protease inhibitors and consumes nitric
oxide, all of which escalate the inflammatory response.42 Myeloperoxidase
levels have been shown to be elevated in patients with diagnosed coronary
artery disease and within atherosclerotic lesions that are prone to rupture.40,43 Myeloperoxidase is also elevated
in patients with chest pain and is predictive of subsequent cardiovascular
events at 3 and 6 months.10 Collectively, the
data from various biomarkers of arterial inflammation have reshaped our understanding
of the disease process. Lifestyle factors such as weight loss and exercise,
and medications including statins, have been shown to reduce the levels of
biomarkers of MI risk.11,44
In this study we show that DG-031 attenuates the capacity of activated
neutrophils to generate leukotriene B4 and myeloperoxidase. Moreover,
the FLAP inhibitor DG-031 appears to have an effect on serum CRP and serum
amyloid A levels that persists after the drug is discontinued. Our data suggest
that DG-031 reduced serum levels of CRP by approximately 25% and amyloid A
by 15%. Furthermore, results from the open-label follow-up study demonstrated
similar effects on CRP from the highest dose of DG-031 after 1 week of treatment.
These results are particularly intriguing because the reduction observed in
CRP is in addition to the beneficial effects that may have been achieved with
statins, which were taken by 85% of the study participants.45,46 While
not anticipated in the design of the study, but recognized by systematic sampling,
the CRP and serum amyloid A results may reflect the possibility of achieving
arterial quiescence. For example, in studies using a brief 12-hour intervention
of intravenous platelet glycoprotein IIb/IIIa blockade, there were benefits
of a 20% mortality reduction still evident 3 years later.47 This
has been attributed to the ability to render a disease plaque less “vulnerable”
to undergo spontaneous rupture.
The highest dose of DG-031 (750 mg/d) increased plasma Lp-PLA2 levels by 9% with a corresponding increase in LDL cholesterol of 8%.
While the clinical implications of elevated Lp-PLA2 remain uncertain,48 the parallel elevation in LDL cholesterol raises
some concern which we have, at least in part, addressed in an animal model
of atherosclerotic disease that examined the effects of DG-031 in apolipoprotein
E mice that were fed a high-fat diet. The drug reduced atherogenesis in mice
suggesting that it may provide protection against atherosclerosis (H.H., unpublished
data, 2004). These data are consistent with a study showing that apolipoprotein
E knockout mice with the low activity version of the 5-lipoxygenase are less
vulnerable to atherogenesis in the aorta than those with the high-activity
variant.37 No effects were observed on LDL
cholesterol by DG-031 in the follow-up study.
We observed a dose-dependent increase in urinary leukotriene E4 levels in response to DG-031. While we expected that inhibition of
FLAP would reduce urinary leukotriene E4 levels (measurements of
leukotriene C4, leukotriene D4, or leukotriene E4 in plasma are unreliable and were not performed), the concentration
of leukotriene E4 in spot urine samples was increased in this study.
While the clinical relevance of the cysteinyl arm of the pathway appears less
relevant in relation to MI risk,38 it is noteworthy
that urinary leukotriene E4 excretion showed no correlation with
efficacy or pharmacokinetic parameters in asthma patients in previous studies
of this FLAP inhibitor (Bay x 1005 study reports No. PH-26825; PH-26199; and
MMRR-1296; unpublished data, 2005).
The FLAP inhibitor DG-031 was well tolerated and there were no serious
adverse events. The assessment of the inhibitory effects of DG-031 on leukotriene
B4 and myeloperoxidase production was performed at steady state
levels of DG-031 (Cmin) and we would therefore expect these effects
to be greater around the peak level (Cmax) of the drug. The follow-up
study addresses this relationship in more depth.
Among the primary markers studied, DG-031 significantly attenuated leukotriene
B4 and myeloperoxidase production in activated leukocytes and reduced
CRP and serum amyloid A. In the follow-up study, plasma myeloperoxidase was
also reduced when measured 6 hours after intake of DG-031 or shortly after
maximum inhibition of leukotriene B4 was reached. In contrast,
plasma Lp-PLA2 and urinary leukotriene E4 secretion
were significantly increased in response to DG-031. We did not observe any
effects from DG-031 on N-tyrosine or on any of the tertiary
markers studied, apart from the intercellular adhesion molecule (P = .02), suggesting that leukotriene B4 may be
more tightly linked to the regulation of myeloperoxidase and adhesion molecules,
but plays little role in the regulation of cytokines such as IL-6 or tumor
necrosis factor α or regulation of mediators more tightly regulated
by these cytokines, such as matrix metalloproteinase 9 and monocyte chemotactic
This study has several limitations. First, we did not collect data on
clinical outcomes in this short-term study. A clinical outcome study will
have to be completed to determine if the effects of DG-031 on biomarkers of
MI risk will translate into decreased risk of MI. Second, the study was conducted
at a single site in Iceland and is the first study, to our knowledge, to use
at-risk variants in FLAP or leukotriene A4 hydrolase for the common
form of MI as inclusion criteria for a clinical trial. While this design has
the potential to improve the power of the study, we do not expect that the
effects of the drug observed in this study to be limited only to those patients
who carried the specific gene variants used for selection herein. In particular,
similar effects are expected for carriers of other at-risk variants in FLAP
or in other genes in this pathway that have yet to be identified. Although
these variants were uncovered in the founder population of Iceland, the variants
of FLAP have now been replicated outside of Iceland.49
In our previous study,3 the at-risk FLAP
haplotype HapA was found to be carried by 29% of Icelandic MI patients compared
with 17% of controls, indicating that the FLAP haplotype confers a risk of
almost 2 (for comparison, elevated cholesterol in the top quartile confers
an average risk of about 1.6 to MI). We have also replicated the FLAP haplotype
in a large US cohort (H.H., unpublished data, 2004) showing that the haplotype
is carried by 30% of US whites who have previously sustained a MI.
When taken together, the data from our MI gene-isolation study and the
clinical trial reported herein show that DG-031 is a safe and well-tolerated
drug that affects a biochemical defect that confers a relative risk of acute
cardiovascular events, which is similar to or greater than that conferred
by the top quartile of LDL cholesterol. Our data suggest that DG-031 reduces
serum levels of CRP, serum amyloid A, and myeloperoxidase and these effects
are in addition to any effects attributed to statins. Our hypothesis is that
this will cause reduction in the risk of MI. To put these results in a historical
context, we believe the promise of the beneficial role of DG-031 in cardiovascular
disease may, at least in part, reflect that of statins in the late 1980s when
it had been shown that they could lower LDL cholesterol but it had not been
shown that lowering LDL cholesterol leads to a decrease in the risk of MI.
A study examining clinical outcomes is in the planning stages to determine
whether DG-031 does indeed affect the risk of MI.
Corresponding Authors: Hakon Hakonarson,
MD, PhD, and Kari Stefansson, MD, PhD, Decode Genetics Inc, Sturlugata 8,
101 Reykjavik, Iceland (firstname.lastname@example.org and email@example.com).
Author Contributions: Gudmundur Thorgeirsson
had full access to all of the data in the study and takes responsibility for
the integrity of the data and the accuracy of the data analysis.
Study concept and design: Hakonarson, Thorvaldsson,
Zink, Manolescu, Kristinsson, Topol, Gulcher, Kong, Gurney, Gudmundur Thorgeirsson,
Acquisition of data: Hakonarson, Helgadottir,
Andresdottir, Arnar, Andersen, Sigurdsson, Gestur Thorgeirsson, Jonsson, Agnarsson,
Bjornsdottir, Gottskalksson, Einarsson, Gudmundsdottir, Adalsteinsdottir,
Gudmundsson, Kristjansson, Hardarson, Kristinsson, Kong, Gudmundur Thorgeirsson.
Analysis and interpretation of data: Hakonarson,
Thorvaldsson, Gudbjartsson, Zink, Kristinsson, Topol, Kong, Gudmundur Thorgeirsson,
Drafting of the manuscript: Hakonarson, Thorvaldsson,
Andresdottir, Jonsson, Bjornsdottir, Einarsson, Adalsteinsdottir, Kristinsson,
Topol, Kong, Stefansson.
Critical revision of the manuscript for important
intellectual content: Hakonarson, Thorvaldsson, Helgadottir, Gudbjartsson,
Zink, Manolescu, Arnar, Andersen, Sigurdsson, Gestur Thorgeirsson, Agnarsson,
Gottskalksson, Gudmundsdottir, Gudmundsson, Kristjansson, Hardarson, Kristinsson,
Topol, Gulcher, Kong, Gurney, Gudmundur Thorgeirsson, Stefansson.
Statistical analysis: Hakonarson, Thorvaldsson,
Gudbjartsson, Zink, Manolescu, Topol, Kong, Stefansson.
Obtained funding: Hakonarson, Gulcher, Stefansson.
Administrative, technical, or material support:
Hakonarson, Thorvaldsson, Sigurdsson, Gestur Thorgeirsson, Agnarsson, Einarsson,
Gudmundsson, Kristjansson, Hardarson, Kristinsson, Topol, Gulcher, Gurney,
Study supervision: Hakonarson, Andresdottir,
Adalsteinsdottir, Topol, Gulcher, Kong, Gudmundur Thorgeirsson.
Financial Disclosures: Gudmundur Thorgeirsson
owns stock in Decode Genetics. No other authors reported financial disclosures.
Funding/Support: The study was sponsored by
Decode Genetics Inc.
Role of the Sponsor: The study reported herein
was designed by Decode Genetics and conducted by Decode’s clinical subsidiary,
Encode. All clinical assessment was performed by the studýs principal
investigator (Gudmundur Thorgeirsson, MD, PhD) and the participating cardiologists
at Landspitali University Hospital, including those in private practice. Data
management, analysis, and interpretation were performed by Decode. The manuscript
was written by the principal study authors and approved for submission by
all authors. Decode’s statisticians Sverrir Thorvaldsson, Augustine
Kong, Florian Zink, and Daniel Gudbjartsson performed the statistical analysis
of the study.
Independent Statistical Analysis: Kristján
Jónasson, PhD, from the Department of Mathematics, University of Iceland,
Reykjavik, was given access to all of the data, including data on medication
and biomarker measurements. Dr Jónasson completed a thorough check
of the methods and data analysis, which included reanalysis of all experimental
data. Dr Jónasson confirms that the results presented herein are both
statistically correct and in accordance with original data.
Acknowledgment: We are grateful to the patients
who participated and made the study possible. Special thanks to the study
management, regulatory, clinical, monitoring and PK laboratory personnel at
Encode, and to the pharmacogenomics and informatics groups at Decode. We also
thank the nurses and other study personnel at the Icelandic Heart Association
for their contributions to the study.